1. Field of the Invention
The present invention generally relates to computer-implemented optimization models for solution of problems and, more particularly, to an approach for generating alternative representations for an optimization model while keeping model parameters at an acceptable, pre-determined accuracy threshold.
2. Background Description
Real-world modeling problems often result in an implementation that makes the model instances intractable due to computationally prohibitive data size and structural complexity. The prior art solutions to such large problems involved simplification of the model by either aggregating the data or simplifying the model assumptions. Hence, the resulting solution is sub-optimal due to both data aggregation and model simplification, and even solving smaller sized problems results in sub-optimal outcomes. As a result, the prior art solutions are not fully satisfactory.